The use of deep learning on endoscopic images to assess the response of rectal cancer after chemoradiation

H.E. Haak, X.P. Gao, M. Maas*, S. Waktola, S. Benson, R.G.H. Beets-Tan, G.L. Beets, M. van Leerdam, J. Melenhorst*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Web of Science)
Original languageEnglish
Pages (from-to)3592-3600
Number of pages9
JournalSurgical endoscopy and other interventional techniques
Volume36
Issue number5
Early online date12 Oct 2021
DOIs
Publication statusPublished - May 2022

Keywords

  • Rectal cancer
  • Deep learning
  • Response evaluation
  • Organ preservation
  • Watch-and-wait approach
  • Artificial intelligence
  • CONVOLUTIONAL NEURAL-NETWORKS
  • CLINICAL COMPLETE RESPONDERS
  • GASTROINTESTINAL ENDOSCOPY
  • ARTIFICIAL-INTELLIGENCE
  • CLASSIFICATION
  • PRESERVATION
  • SELECTION
  • SOCIETY
  • WATCH

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